Where Do Alphas Come From?: A New Measure of the Value of Active Investment Management

40 Pages Posted: 26 Mar 2008

See all articles by Andrew W. Lo

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering; Santa Fe Institute

Multiple version iconThere are 3 versions of this paper

Date Written: May 8, 2007


The value of active investment management is traditionally measured by alpha, beta, tracking error, and the Sharpe and information ratios. These are essentially static characteristics of the marginal distributions of returns at a single point in time, and do not incorporate dynamic aspects of a manager's investment process. In this paper, I propose a new measure of the value of active investment management that captures both static and dynamic contributions of a portfolio manager's decisions. The measure is based on a decomposition of a portfolio's expected return into two distinct components: a static weighted-average of the individual securities' expected returns, and the sum of covariances between returns and portfolio weights. The former component measures the portion of the manager's expected return due to static investments in the underlying securities, while the latter component captures the forecast power implicit in the manager's dynamic investment choices. This measure can be computed for long-only investments, long/short portfolios, and asset allocation rules, and is particularly relevant for hedge-fund strategies where both components are significant contributors to their expected returns, but only one should garner the high fees that hedge funds typically charge. Several analytical and empirical examples are provided to illustrate the practical relevance of these new measures.

Keywords: Alpha, Beta, Performance Attribution, Active Management, Hedge Funds

JEL Classification: G11, G12

Suggested Citation

Lo, Andrew W., Where Do Alphas Come From?: A New Measure of the Value of Active Investment Management (May 8, 2007). Available at SSRN: https://ssrn.com/abstract=985127 or http://dx.doi.org/10.2139/ssrn.985127

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering ( email )

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HOME PAGE: http://web.mit.edu/alo/www

Santa Fe Institute

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